A plant is stabilized by its root system. In congested urban cities such as Hong Kong, ground trenching is frequently seen due to the installation of utility lines along the roadside. Soil nailing, which involves soil...A plant is stabilized by its root system. In congested urban cities such as Hong Kong, ground trenching is frequently seen due to the installation of utility lines along the roadside. Soil nailing, which involves soil coring in slopes, is a common solution to improve the slope stability. However, both activities inevitably pose a risk to the integrity of any root sys- tems present, and thus reduce the root anchorage. To prevent or minimize such damage, a careful design of the excava- tion/drilling location is of prime importance. Ground penetrating radar （GPR） provides a non-destructive method for locating roots by examining the contrast between the dielectric properties of the roots and the surrounding soil. To examine the perfor- mance of GPR and promote its use in Hong Kong, a test bed was prepared using local materials to create a controlled envi- ronment in which to conduct a series of systematic tests evaluating the performance of a 900 MHz GPR. The reflected radar- grams were subject to the influence of the following factors： size and depth of roots, horizontal distance between roots, and contrast between the root and soil water content. Correlations between root size and a number of waveform parameters were also explored. Limiting values for root size, root embedded depth, horizontal separation distance between roots, and water content contrast between root and soil were obtained. A significant correlation was found between the root diameter and time travel parameter T2 （p〈0.001, t=0.795）. Because GPR root detection is highly site-specific, this study provides a local refer- ence for GPR performance in the Hong Kong environment. The findings demonstrate that the 900 MHz GPR is applicable in Hong Kong for the detection of main roots.展开更多
The case–cohort design has been widely used to reduce the cost of covariate measurements in large cohort studies.In this paper,we study the high-dimensional accelerated failure time(AFT)model under the case–cohort d...The case–cohort design has been widely used to reduce the cost of covariate measurements in large cohort studies.In this paper,we study the high-dimensional accelerated failure time(AFT)model under the case–cohort design.Based on?0-regularization and a newly defined weight function,we propose a weighted least squares procedure for variable selection and parameter estimation.Computationally,we develop a support detection and root finding(SDAR)algorithm,where the support is first determined based on the primal and dual information,then the estimator is obtained by solving the weighted least squares problem restricted to the estimated support.We show the proposed algorithm is essentially one Newton-type algorithm,thus it is more efficient and stable compared with other regularized methods.Theoretically,we establish a sharp error bound for the solution sequences generated from the proposed method.Furthermore,we propose an adaptive version of the proposed SDAR algorithm,which determines the support size of the estimated coefficient in a data-driven manner.Extensive simulation studies demonstrate the superior performance of the proposed procedures,especially for the computational efficiency.As an illustration,we apply the proposed method to a malignant breast tumor gene expression data.展开更多
基金the Research Grants Council of the Hong Kong Special Administrative Region (HKSAR) (Grant Nos. HKUST9/CRF/ 09, HKUST6/CRF/12R)
文摘A plant is stabilized by its root system. In congested urban cities such as Hong Kong, ground trenching is frequently seen due to the installation of utility lines along the roadside. Soil nailing, which involves soil coring in slopes, is a common solution to improve the slope stability. However, both activities inevitably pose a risk to the integrity of any root sys- tems present, and thus reduce the root anchorage. To prevent or minimize such damage, a careful design of the excava- tion/drilling location is of prime importance. Ground penetrating radar （GPR） provides a non-destructive method for locating roots by examining the contrast between the dielectric properties of the roots and the surrounding soil. To examine the perfor- mance of GPR and promote its use in Hong Kong, a test bed was prepared using local materials to create a controlled envi- ronment in which to conduct a series of systematic tests evaluating the performance of a 900 MHz GPR. The reflected radar- grams were subject to the influence of the following factors： size and depth of roots, horizontal distance between roots, and contrast between the root and soil water content. Correlations between root size and a number of waveform parameters were also explored. Limiting values for root size, root embedded depth, horizontal separation distance between roots, and water content contrast between root and soil were obtained. A significant correlation was found between the root diameter and time travel parameter T2 （p〈0.001, t=0.795）. Because GPR root detection is highly site-specific, this study provides a local refer- ence for GPR performance in the Hong Kong environment. The findings demonstrate that the 900 MHz GPR is applicable in Hong Kong for the detection of main roots.
基金Supported by the National Natural Science Foundation of China(Grant Nos.12371274,12271459)National Social Science Foundation of China(Grant No.24CTJ036)+1 种基金Natural Science Foundation of Hubei Province(Grant No.2021CFB502)the Fundamental Research Funds for the Central Universities,Zhongnan University of Economics and Law(Grant No.2722024BY024)。
文摘The case–cohort design has been widely used to reduce the cost of covariate measurements in large cohort studies.In this paper,we study the high-dimensional accelerated failure time(AFT)model under the case–cohort design.Based on?0-regularization and a newly defined weight function,we propose a weighted least squares procedure for variable selection and parameter estimation.Computationally,we develop a support detection and root finding(SDAR)algorithm,where the support is first determined based on the primal and dual information,then the estimator is obtained by solving the weighted least squares problem restricted to the estimated support.We show the proposed algorithm is essentially one Newton-type algorithm,thus it is more efficient and stable compared with other regularized methods.Theoretically,we establish a sharp error bound for the solution sequences generated from the proposed method.Furthermore,we propose an adaptive version of the proposed SDAR algorithm,which determines the support size of the estimated coefficient in a data-driven manner.Extensive simulation studies demonstrate the superior performance of the proposed procedures,especially for the computational efficiency.As an illustration,we apply the proposed method to a malignant breast tumor gene expression data.
